OpenSearch Tutorial Application

This project demonstrates various OpenSearch search capabilities through a web application built with Cloudscape React and AWS services.

Overview

The application provides examples of different search functionalities using Amazon OpenSearch Service, including:

• Keyword Search
  • Prefix Match
  • Multi Match
  • Fuzzy Search
  • Minimum Should Match
  • Wildcard Match
  • Range Filter
  • Compound Queries
  • Aggregations
• Semantic Search (Disk vs In-Memory modes)
• Hybrid Search (Disk vs In-Memory modes)
• Document Indexing

Architecture

The application is built using:

• Frontend: React with Cloudscape Design System
• Backend: AWS Lambda functions / API Gateway
• Search: Amazon OpenSearch Service
• Infrastructure: AWS CDK
• Hosting: AWS App Runner
• Authentication: Amazon Cognito

Prerequisites

• Node.js 16 or later
• Python 3.10 or later
• AWS CDK v2.91.0
• AWS CLI configured with appropriate credentials

Deployment Steps

1. Search for Cloudshell service on the AWS Console and follow the steps below to clone the github repository

2. Clone the sample-for-amazon-opensearch-tutorials-101 repository using the below command:

git clone https://github.com/aws-samples/sample-for-amazon-opensearch-tutorials-101.git

3. Head on to the sample-for-amazon-opensearch-tutorials-101 folder using the below command

cd sample-for-amazon-opensearch-tutorials-101

4. Deploy the infrastructure:

sh installer.sh

Note: triggering builder.sh directly runs the script in Cloudshell which could terminate due to inactivity. We recommend running installer.sh which triggers a codebuild job.

5. Press Enter to confirm deployment

6. The deployment takes 30 minutes to create all resources. You can track its progress on Cloudformation

7. Once done, head to AppRunner to obtain the application url

8. Get started by first creating your account on the Opensearch tutorial Application

9. To test out Keyword search functionality, first index some products on the Opensearch tutorial application. Every feature is also accompanied by a guide, best practices and links to the Opensearch documentation. You could also index a custom product.

10. Updated features

Note: The builder script will:

• Deploy the Lambda Layer Stack
• Build and deploy the OpenSearch Proxy Stack
• Build and deploy the UI container
• Deploy the App Runner hosting stack

Environment Configuration

The application supports three environments:

• dev
• qa
• sandbox

Configuration for each environment is managed in cdk.json.

Cleanup

Delete all the deployed resources

cdk destroy

Project Structure

.
├── app.py                      # CDK app entry point
├── artifacts/
│   ├── index_lambda/          # Document indexing function
│   ├── opensearch-app-ui/     # React frontend application
│   └── search_lambda/         # Search functionality
├── builder.sh                 # Deployment automation script
├── search_tutorials/          # CDK infrastructure stacks
└── requirements.txt           # Python dependencies

Security

The application implements several security measures:

• Private VPC for OpenSearch domain
• AWS IAM roles and policies for service access
• HTTPS enforcement for all API endpoints
• Cognito user authentication

Development

Frontend Development

The UI is located in artifacts/opensearch-app-ui/ and can be run locally:

cd artifacts/opensearch-app-ui
npm install
npm run dev

Infrastructure Development

Infrastructure is defined using AWS CDK in the search_tutorials/ directory:

• lambda_layer_stack.py: Lambda layers for dependencies

• opensearch_proxy_stack.py: OpenSearch domain and Lambda functions

• apprunner_hosting_stack.py: UI hosting configuration

• DeepWiki Docs : https://deepwiki.com/aws-samples/sample-for-amazon-opensearch-tutorials-101